Radiation Oncologist

Handshake; United States; À distance; USD 148 000 - 210 000; Temps partiel

Résumé du poste

Handshake is seeking Radiation Oncologists to support AI research through flexible, part-time contract work. You will apply your clinical training in contouring, dose prescription, and multidisciplinary cancer care to evaluate AI-generated content and provide feedback from a practicing radiation oncologist perspective.

The program operates year-round with project opportunities across areas of expertise. This is an ongoing, project-based role you can take on alongside your current position, all

Qualifications

• MD/DO or equivalent medical degree.
• Completed residency in radiation oncology.
• US medical licensure to practice medicine.

Responsabilités

• Create expert-level AI tasks based on clinical workflows such as contouring, planning, and dose selection.
• Review AI outputs for clinical accuracy and safety in radiation oncology.
• Provide structured feedback to improve AI model performance.
• Work remotely at your own pace with no set schedule or minimum hour requirement.

Connaissances

Clinical expertise

Written communication

Remote work independence

Formation

MD/DO or equivalent

Residency in radiation oncology

Outils

Contour software

Treatment planning systems

Description du poste

Radiation Oncologist

Up to $130/hr Depending on the project Ph.D's , Postdocs Remote Part-time Flexible hours

Opportunity Overview

Handshake is looking for radiation oncologists to support AI research through flexible, part-time contract work. This is not a traditional job. You'll draw on your clinical training and hands-on experience in radiation oncology, including treatment planning, target volume and organ-at-risk contouring, dose prescription, and multidisciplinary cancer care, to evaluate AI-generated content and provide feedback that helps AI reason like a practicing radiation oncologist. The Handshake AI program runs year-round, with project opportunities opening periodically across different areas of expertise. This is an ongoing, project-based opportunity you can take on alongside your current role.

What You'll Do

• Use your clinical expertise to create expert-level tasks that todays top AI models can't solve, based on real clinical workflows such as target volume and organ-at-risk contouring, simulation CT and imaging review, dose and fractionation selection, plan evaluation, and treatment planning
• Review and evaluate AI-generated responses for clinical accuracy, patient safety, and alignment with current radiation oncology practice and guidelines
• Provide clear, structured written feedback to help improve AI model performance
• Work remotely and complete tasks at your own pace, with no set schedule or minimum hour requirement

Qualifications

• Degree and clinical training: Completed MD, DO, or equivalent medical degree
• Completed residency training in radiation oncology
• Licensure: Currently licensed to practice medicine in the United States
• Clinical depth: Working knowledge in one or more of the following areas: Contouring of target volumes and organs at risk (e.g., head and neck, thoracic, breast, GI, GU, CNS) External beam radiotherapy, including IMRT, VMAT, and image-guided radiotherapy Stereotactic radiosurgery and stereotactic body radiotherapy (SRS/SBRT) Brachytherapy Proton and particle therapy Palliative radiotherapy and radiation oncology emergencies Pediatric or hematologic radiation oncology
• Additional qualifications (not required, but strengthen your application) Board certification or board eligibility in radiation oncology, or fellowship training in a subspecialty Experience at an academic medical center or comprehensive cancer center, familiarity with treatment planning systems and contouring software, peer-reviewed publications, or involvement in clinical research

Required for all applicants

• Must have US work authorization
• Strong written communication and attention to detail
• Ability to explain complex radiation oncology concepts clearly
• Ability to work independently in a remote, asynchronous environment